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An Image Segmentation Method for Quasi-circular Immune Cells

机译:准圆形免疫细胞的图像分割方法

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摘要

Aiming at the characteristic of actual quasi-circular immune cell images, this paper presents the method of quasi-circular immune cell images segmentation based on Otsu threshold and thinning algorithm. The image is first converted color space form RGB to YIQ. Then the image is segmented by Otsu threshold algorithm. And then the erosion and dilation of morphological filter are used to process the image. Finally, the Zhang-Suen thinning algorithm is employed to extract the cellȁ9;s skeleton, which is the center of the quasi-circular immune cell. According to the thinning times, we can obtain the radius value of the quasi-circular immune cell, and the overlapping quasi-circular immune cells are separated. Experimental results show this method works successfully in the segmentation of quasi-circular immune cell images.
机译:针对实际的准圆形免疫细胞图像特征,提出了基于Otsu阈值和细化算法的准圆形免疫细胞图像分割方法。首先将图像从RGB转换为色彩空间,然后再转换为YIQ。然后通过Otsu阈值算法对图像进行分割。然后利用形态学滤镜的腐蚀和膨胀来处理图像。最后,采用Zhang-Suen稀疏算法来提取细胞的骨架,该骨架是准圆形免疫细胞的中心。根据细化时间,可以得到准圆形免疫细胞的半径值,并将重叠的准圆形免疫细胞分离。实验结果表明,该方法在准圆形免疫细胞图像分割中取得了成功。

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